Gastric Intestinal Vascular Ectasia Syndrome: Findings on Capsule Endoscopy
Bibliographic record
Abstract
Introduction Gastric antral vascular ectasia (GAVE) syndrome has been recognized as an important cause of gastrointestinal hemorrhage [ 1 ] [ 2 ]. Histopathologically, GAVE is characterized by superficial fibromuscular hyperplasia of the gastric antral mucosa, with capillary ectasia and microvascular thrombosis in the lamina propria. Although it is helpful to make a pathological diagnosis, the most reliable means of diagnosing GAVE and other areas of angioectasia in the gastrointestinal tract is by direct endoscopic visualization [ 2 ]. Since GAVE was first described, there have been several reports of patients with similar endoscopic findings in other regions of the gastrointestinal tract, including the cardia [ 3 ], duodenum [ 4 ], colon [ 5 ] [ 6 ], and rectum [ 7 ]. Terms such as “watermelon cecum”, “watermelon colon”, and “watermelon rectum” have been coined to describe such lesions. We present here two patients with GAVE and anemia who we investigated using the Given M2A wireless capsule video system (Given Imaging Ltd., Yoqneam, Israel). We have described the technique of capsule endoscopy performed in our center previously and also the classification criteria for the resulting findings [ 8 ].
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".